code: def _split_docstring(value):
      headers = {}
      current_header = ""
      current_lines = []
      lines = value.split("\n")
      index = 0
      while index < len(lines):
          if (
              index + 1 < len(lines)
              and len(lines[index + 1].strip(" ")) > 0
              and len(lines[index + 1].strip(" ").strip("-")) == 0
          ):
              headers[current_header] = current_lines
              current_header = lines[index].strip(" ")
              current_lines = []
              index = index + 1
          else:
              current_lines.append(lines[index])
          index = index + 1
      headers[current_header] = current_lines
      return headers
  
file_path: netron/tools/sklearn_metadata.py
imports: import json
  import os
  import pydoc
  import re
label_desc: Use image node_id 1 for calling a global function with example usage: _split_docstring(value) and returns: headers